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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# tsfgrnn
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[![R-CMD-check](https://github.com/franciscomartinezdelrio/tsfgrnn/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/franciscomartinezdelrio/tsfgrnn/actions/workflows/R-CMD-check.yaml)
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The goal of tsfgrnn is to forecast time series using GRNN regression.
## Installation
You can install the released version of tsfgrnn from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("tsfgrnn")
```
And the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("franciscomartinezdelrio/tsfgrnn")
```
## Example
This is a basic example which shows how to forecast with tsfgrnn:
```{r example}
library(tsfgrnn)
pred <- grnn_forecasting(USAccDeaths, h = 12)
pred$prediction # To see a time series with the forecasts
plot(pred) # To see a plot with the forecast
```
To know more, the open access paper [Francisco Martinez et al. (2022)](https://doi.org/10.1016/j.neucom.2021.12.028) describes the package. Also, you can read the package's vignette.
## Acknowledgements
Funds: This work was partially supported by the project TIN2015-68854-R (FEDER Founds) of the Spanish Ministry of Economy and Competitiveness.